Impacts of Aggregation Methods and Trophospecies Number on the Structure and Function of Marine Food Webs

Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches. However, species aggregation will affect not only the complexity of modeling process but also the accuracy of models’ outputs. Selection of aggregation methods and the number of trophospecies are the keys to study the simplification of food web. In this study, three aggregation methods, including taxonomic aggregation (TA), structural equivalence aggregation (SEA), and self-organizing maps (SOM), were analyzed and compared with the linear inverse model–Markov Chain Monte Carlo (LIM-MCMC) model. Impacts of aggregation methods and trophospecies number on food webs were evaluated based on the robustness and unitless of ecological network indices. Results showed that aggregation method of SEA performed better than the other two methods in estimating food web structure and function indices. The effects of aggregation methods were driven by the differences in species aggregation principles, which will alter food web structure and function through the redistribution of energy flow. According to the results of mean absolute percentage error (MAPE) which can be applied to evaluate the accuracy of the model, we found that MAPE in food web indices will increase with the reducing trophospecies number, and MAPE in food web function indices were smaller and more stable than those in food web structure indices. Therefore, trade-off between simplifying food webs and reflecting the status of ecosystem should be considered in food web studies. These findings highlight the importance of aggregation methods and trophospecies number in the analysis of food web simplification. This study provided a framework to explore the extent to which food web models are affected by different species aggregation, and will provide scientific basis for the construction of food webs.